Over the last 10 years within emergency and acute care there has been a rapid movement towards ‘near patient’ testing and early investigation with the presumption that earlier investigation will give rise to early decision making and hence reduced length of stay in hospital and better outcomes.

Dementia is recognised as one of the greatest public health threats of our time, both in the UK and globally. Alzheimer’s disease is the most common cause of dementia, but drug development has recently failed [1].

Employing machine learning (ML) algorithms is a promising way of exploring the complex architecture of big data in genetics. Several methods exist for solving classification problems like case-control and outcome groups in ML.

Background. In spite of substantial progress in the development of sophisticated methodologies for disease detection, they are often difficult to apply at the point of need, and some can also be time-consuming and/or expensive.